Databricks Partnership: Driving Business Value

2023-07-21T16:24:55+00:00October 3rd, 2022|Categories: Artificial Intelligence, Assessments, Data Extraction, Data Science, In the press, Machine Learning, Partnership, Press Releases|

Databricks Partnership: Driving Business Value Machine learning services built on Databricks’ Lakehouse Platform provide expedited value to clients to solve their big data problems. NLP Logix, one of the fastest growing custom machine learning/artificial intelligence companies in the United States, today announced they have partnered with Databricks, the lakehouse company, to drive business value by unifying data and artificial intelligence (AI).  NLP Logix brings over a dozen years of experience in developing and deploying custom machine learning and business automation solutions across multiple industries including defense, human resources, non-profit, financial services and others. "At NLP Logix we say that "Data [...]

Serious About Safety – Job Site Accident Probability

2022-07-05T18:28:48+00:00May 11th, 2022|Categories: Assessments, Case Studies, Predictive Modeling|

Always Serious About Safety - Job Site Accident Probability A Case Study with Miller Electric Company, Jacksonville, FL Background Context In 2021, NLP Logix client Miller Electric sought to develop a method to better understand how to leverage their extensive data to identify safety related opportunities and drive awareness of the underlying factors that could lead to safety issues. In support of this initiative, Miller Electric and NLP Logix engaged in several discovery workshops as part of NLP Logix’s 10Q Assessment methodology where questions were posed with a focus on understanding underlying trends in reported injuries. Safety Culture has always been a priority at Miller Electric with [...]

Debunking Myths – Is more data always better?

2022-07-20T15:45:26+00:00May 10th, 2022|Categories: Assessments, Data Science|Tags: , , |

Is more data always better? More data isn’t always better.  Sometimes it’s just more.  Collecting large amounts of data without strategy can often create massive data set tangles to unravel.  Large data dumps tend to waste time and cause frustration if the information presented is not relevant. To avoid snags, smaller data sets can be utilized to effectively identify insights.    Over the past decade, Ben Webster, NLP Modeling and Analytics Team Lead, has seen a shift in how teams interact with data.  The question used to be:  “Do I have enough data?” Most companies were just at the point of sufficient data for machine learning tasks. The better [...]

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